Bayesian accrual modeling and prediction in multicenter clinical trials with varying center activation times.
Pharm Stat
; 19(5): 692-709, 2020 09.
Article
in En
| MEDLINE
| ID: mdl-32319194
ABSTRACT
Investigators who manage multicenter clinical trials need to pay careful attention to patterns of subject accrual, and the prediction of activation time for pending centers is potentially crucial for subject accrual prediction. We propose a Bayesian hierarchical model to predict subject accrual for multicenter clinical trials in which center activation times vary. We define center activation time as the time at which a center can begin enrolling patients in the trial. The difference in activation times between centers is assumed to follow an exponential distribution, and the model of subject accrual integrates prior information for the study with actual enrollment progress. We apply our proposed Bayesian multicenter accrual model to two multicenter clinical studies. The first is the PAIN-CONTRoLS study, a multicenter clinical trial with a goal of activating 40 centers and enrolling 400 patients within 104 weeks. The second is the HOBIT trial, a multicenter clinical trial with a goal of activating 14 centers and enrolling 200 subjects within 36 months. In summary, the Bayesian multicenter accrual model provides a prediction of subject accrual while accounting for both center- and individual patient-level variation.
Key words
Full text:
1
Database:
MEDLINE
Main subject:
Clinical Trials as Topic
/
Models, Statistical
/
Multicenter Studies as Topic
Type of study:
Clinical_trials
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
Pharm Stat
Journal subject:
FARMACOLOGIA
Year:
2020
Type:
Article
Affiliation country:
United States